Summary from listing
The role develops and executes data-mining and risk-analytics projects to detect fraud, anti-corruption, and trading-desk misconduct. Responsibilities include designing CRISP-DM models, ingesting data into LZ or DWH environments, configuring adaptive risk alerts, building machine-learning and neural-network models, and calibrating scoring rules to reduce false positives. The position requires a degree in Systems Engineering, Computer Science, or Statistics and 1–3 years of experience in data analysis, modeling, statistical techniques, databases, data ingestion, or fraud and compliance projects.
